When should a negative #COVID19 test be ignored? Let& #39;s say a doctor sees a patient w/ possible #COVID19. She highly suspects infection because patient has cough, chest pain, abnormal chest x-ray, fever, diarrhea & known exposure. Doc puts the chance at 90%. Next... (1/5)

... a throat swab is checked but comes back negative. Let& #39;s assume that throat swab is 90% sensitive & specific (in reality, it& #39;s lower than that, but let& #39;s assume a best case scenario). What is the chance this patient still has #COVID19? Read on... (2/5)

Turns out there& #39;s math for this. We use Bayes theorem. Good news is no need to memorize the equation. Just punch the numbers into this app (one of many): https://apps.apple.com/us/app/bayes-post-test-probability-calculator/id371920137.">https://apps.apple.com/us/app/ba... Pic shows scenario where pre-test likelihood is 90% & test is 90% sensitivity/specific. Next... (3/5)

... hit "run." If test comes back +ive then chance of #COVID19 rises to ~99%. But if it& #39;s negative, does that rule-out infection? No. Even with a negative test, still a 50% chance of infection. Need to test again, or test elsewhere (like in stool, in deep airway), or just...(4/5)

...assume patient has #COVID19 because clinical suspicion so high we ignore test result. In reality, real test is prob not 90% accurate. That& #39;s why clinical gestalt is so vital. The wisdom of clinicians should override test result unless & until there& #39;s 100% accurate test. (5/5)